Journal of theCommons
The peer-reviewed journal of Aitele Research — the breakthroughs of the Commons, and the use cases built upon them. Closed to the Commons while a result matures; opened to the world the moment it reaches the field.
Preprints
Latest preprints
New research, released as it is written and placed under Commons review ahead of formal peer review. The journal updates continuously; finalized work is later collected into a numbered edition.
Closed-Form Figure Placement — Training-Free Document Layout
Where should a figure go? Most layout engines either drop figures at the end of a document, spread them mechanically, or anchor them to the first place the text says "Figure 1". We ask whether the *document's own statistics* can decide, in closed form, without any training. In the spirit of Reverse Synthetic Networks — where the data synthesises the model directly — we synthesise each figure's position from three statistics of the manuscript itself: the TF-IDF affinity between the figure's caption and each block of running text, the proximity to any explicit lexical reference, and a small set of layout priors. There is no loss function, no gradient, and no learned parameters. On a controlled 600-document corpus (1,903 figures) drawn from the Aitele Commons' research domains, the closed-form placer reaches 92.5% top-1 placement accuracy and a mean position error of 0.18 sections, against 60.9% for a reference-only baseline and ~22% for content-blind baselines. The decisive result is on unreferenced figures — those the prose never names: here the closed-form affinity recovers 85.1% of placements, where the reference-only method collapses to 21.7% (essentially chance). Closed-form caption–text affinity, in other words, supplies the reference the author forgot to write. The same machinery groups related figures into multi-panel composites (pair-F1 0.99, 97.7% of groups recovered exactly), assigns column-spanning width for a balanced two-column page, and — extended to in-text citations — places each reference at the sentence it supports with 90.6% accuracy (vs ~15% for position-based baselines) and splices the grouped markers into the prose. The library ships with a 34-test suite (unit, edge-case, randomised-invariant, determinism, and a 1,200-block stress test). We report the method, the experiment, and its limitations honestly: the corpus is topically separated, the metrics are layout proxies rather than human aesthetic judgement, and page-overflow is out of scope.
Closed-Form Related-Content Recommendation — with an Honest Relevance Gate
Closed-Form Reviewer Matching — Conflict Exclusion, Fit Gate, Load Balancing
Training-Free Archetype Typing of Conspiracy Networks from Call-Detail Records (Sanjaal)
Breakthroughs and the implementations built upon them — the peer-reviewed record of the Commons.
StochastiCore: A Complete GPU Architecture Based on Stochastic Computing With Yosys-Verified Synthesis, Gate-Level Power, and a Deterministic-Generator Study
Financial Markets as Programmable Computation Substrates
A uniform verdict on the K2-18 b dimethyl-sulfide claim and a population-scale biosignature census of the JWST exoplanet atmosphere archive
Heavy-hex-native bivariate bicycle codes from evolutionary and LLM-guided search
Enforcing Detailed Balance Reveals Systematic Thermodynamic Inconsistencies in Whole-Cell Models
Reverse Synthetic Networks: Training-Free Models in Closed Form
The archive